{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "大家好，我是『K同学啊』！\n",
    "\n",
    "今天我将带大家探索一下深度学习在医学领域的应用，**乳腺癌是女性最常见的癌症形式，浸润性导管癌 (IDC) 是最常见的乳腺癌形式。准确识别和分类乳腺癌亚型是一项重要的临床任务，利用深度学习方法识别可以有效节省时间并减少错误。** 我们的数据集是由多张**以 40 倍扫描的乳腺癌 (BCa) 标本的完整载玻片图像**组成。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "🔥本文 GitHub [https://github.com/kzbkzb/Python-AI](https://github.com/kzbkzb/Python-AI) 已收录\n",
    "\n",
    "- 作者：[K同学啊](https://mp.weixin.qq.com/s/NES9RhtAhbX_jsmGua28dA)\n",
    "- 来自专栏：《深度学习100例》-Tensorflow2版本\n",
    "- 数据链接：https://pan.baidu.com/s/1cWMvsl37MOZdxnoOjSGoNQ （提取码：borf）\n",
    "\n",
    "🚀我的环境：\n",
    "\n",
    "- 语言环境：Python3.6.5\n",
    "- 编译器：jupyter notebook\n",
    "- 深度学习环境：TensorFlow2.4.1\n",
    "- 显卡（GPU）：NVIDIA GeForce RTX 3080\n",
    "\n",
    "**如果你是一名深度学习小白可以先看看我这个专门为你写的专栏：[《小白入门深度学习》](https://blog.csdn.net/qq_38251616/category_11188161.html)**\n",
    "\n",
    "1. [小白入门深度学习 | 第一篇：配置深度学习环境](https://mtyjkh.blog.csdn.net/article/details/118575238)\n",
    "2. [小白入门深度学习 | 第二篇：编译器的使用-Jupyter Notebook](https://mtyjkh.blog.csdn.net/article/details/118814364)\n",
    "3. [小白入门深度学习 | 第三篇：深度学习初体验](https://mtyjkh.blog.csdn.net/article/details/119081309)\n",
    "4. [小白入门深度学习 | 第四篇：配置PyTorch环境](https://mtyjkh.blog.csdn.net/article/details/119969393)\n",
    "\n",
    "🚀 往期精彩-卷积神经网络篇：\n",
    "\n",
    "1. [深度学习100例-卷积神经网络（CNN）实现mnist手写数字识别 | 第1天](https://mtyjkh.blog.csdn.net/article/details/116920825) \n",
    "2. [深度学习100例-卷积神经网络（CNN）彩色图片分类 | 第2天](https://mtyjkh.blog.csdn.net/article/details/116978213)\n",
    "3. [深度学习100例-卷积神经网络（CNN）服装图像分类 | 第3天](https://mtyjkh.blog.csdn.net/article/details/116992196)\n",
    "4. [深度学习100例-卷积神经网络（CNN）花朵识别 | 第4天](https://mtyjkh.blog.csdn.net/article/details/117079919)\n",
    "5. [深度学习100例-卷积神经网络（CNN）天气识别 | 第5天](https://mtyjkh.blog.csdn.net/article/details/117186183)\n",
    "6. [深度学习100例-卷积神经网络（VGG-16）识别海贼王草帽一伙 | 第6天](https://mtyjkh.blog.csdn.net/article/details/117331631)\n",
    "7. [深度学习100例-卷积神经网络（VGG-19）识别灵笼中的人物 | 第7天](https://mtyjkh.blog.csdn.net/article/details/117395797)\n",
    "8. [深度学习100例-卷积神经网络（ResNet-50）鸟类识别 | 第8天](https://mtyjkh.blog.csdn.net/article/details/117587326)\n",
    "9. [深度学习100例-卷积神经网络（AlexNet）手把手教学 | 第11天](https://mtyjkh.blog.csdn.net/article/details/117986183)\n",
    "10. [深度学习100例-卷积神经网络（CNN）识别验证码 | 第12天](https://mtyjkh.blog.csdn.net/article/details/118211253)\n",
    "11. [深度学习100例-卷积神经网络（Inception V3）识别手语 | 第13天](https://mtyjkh.blog.csdn.net/article/details/118310170)\n",
    "12. [深度学习100例-卷积神经网络（Inception-ResNet-v2）识别交通标志 | 第14天](https://mtyjkh.blog.csdn.net/article/details/118389790)\n",
    "13. [深度学习100例-卷积神经网络（CNN）实现车牌识别 | 第15天](https://mtyjkh.blog.csdn.net/article/details/118422302)\n",
    "14. [深度学习100例-卷积神经网络（CNN）识别神奇宝贝小智一伙 | 第16天](https://mtyjkh.blog.csdn.net/article/details/118631541)\n",
    "15. [深度学习100例-卷积神经网络（CNN）注意力检测 | 第17天](https://mtyjkh.blog.csdn.net/article/details/118938811)\n",
    "16. [深度学习100例-卷积神经网络（VGG-16）猫狗识别 | 第21天](https://mtyjkh.blog.csdn.net/article/details/119531838)\n",
    "17. [深度学习100例-卷积神经网络（LeNet-5）深度学习里的“Hello Word” | 第22天](https://mtyjkh.blog.csdn.net/article/details/119700804)\n",
    "18. [深度学习100例-卷积神经网络（CNN）3D医疗影像识别 | 第23天](https://mtyjkh.blog.csdn.net/article/details/119899570)\n",
    "19. [深度学习100例 | 第24天-卷积神经网络（Xception）：动物识别](https://blog.csdn.net/qq_38251616/article/details/120073717)\n",
    "20. [深度学习100例 | 第25天-卷积神经网络（Xception）：中文手写数字识别](https://mtyjkh.blog.csdn.net/article/details/120149868)\n",
    "\n",
    "🚀 往期精彩-循环神经网络篇：\n",
    "\n",
    "1. [深度学习100例-循环神经网络（RNN）实现股票预测 | 第9天](https://mtyjkh.blog.csdn.net/article/details/117752046)\n",
    "2. [深度学习100例-循环神经网络（LSTM）实现股票预测 | 第10天](https://mtyjkh.blog.csdn.net/article/details/117907074)\n",
    "\n",
    "🚀 往期精彩-生成对抗网络篇：\n",
    "\n",
    "1. [深度学习100例-生成对抗网络（GAN）手写数字生成 | 第18天](https://mtyjkh.blog.csdn.net/article/details/118995896)\n",
    "2. [深度学习100例-生成对抗网络（DCGAN）手写数字生成 | 第19天](https://mtyjkh.blog.csdn.net/article/details/119133575)\n",
    "3. [深度学习100例-生成对抗网络（DCGAN）生成动漫小姐姐 | 第20天](https://mtyjkh.blog.csdn.net/article/details/119182578)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# 一、设置GPU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "gpus = tf.config.list_physical_devices(\"GPU\")\n",
    "\n",
    "if gpus:\n",
    "    gpu0 = gpus[0] #如果有多个GPU，仅使用第0个GPU\n",
    "    tf.config.experimental.set_memory_growth(gpu0, True) #设置GPU显存用量按需使用\n",
    "    tf.config.set_visible_devices([gpu0],\"GPU\")\n",
    "    \n",
    "import matplotlib.pyplot as plt\n",
    "import os,PIL,pathlib\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import warnings\n",
    "from tensorflow import keras\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")             #忽略警告信息\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False    # 用来正常显示负号"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# 二、导入数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. 导入数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "图片总数为： 13403\n"
     ]
    }
   ],
   "source": [
    "import pathlib\n",
    "\n",
    "data_dir = \"./32-data\"\n",
    "data_dir = pathlib.Path(data_dir)\n",
    "image_count = len(list(data_dir.glob('*/*')))\n",
    "print(\"图片总数为：\",image_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size = 16\n",
    "img_height = 50\n",
    "img_width  = 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 13403 files belonging to 2 classes.\n",
      "Using 10723 files for training.\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "关于image_dataset_from_directory()的详细介绍可以参考文章：https://mtyjkh.blog.csdn.net/article/details/117018789\n",
    "\"\"\"\n",
    "train_ds = tf.keras.preprocessing.image_dataset_from_directory(\n",
    "    data_dir,\n",
    "    validation_split=0.2,\n",
    "    subset=\"training\",\n",
    "    seed=12,\n",
    "    image_size=(img_height, img_width),\n",
    "    batch_size=batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 13403 files belonging to 2 classes.\n",
      "Using 2680 files for validation.\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "关于image_dataset_from_directory()的详细介绍可以参考文章：https://mtyjkh.blog.csdn.net/article/details/117018789\n",
    "\"\"\"\n",
    "val_ds = tf.keras.preprocessing.image_dataset_from_directory(\n",
    "    data_dir,\n",
    "    validation_split=0.2,\n",
    "    subset=\"validation\",\n",
    "    seed=12,\n",
    "    image_size=(img_height, img_width),\n",
    "    batch_size=batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['0', '1']\n"
     ]
    }
   ],
   "source": [
    "class_names = train_ds.class_names\n",
    "print(class_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 检查数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(16, 50, 50, 3)\n",
      "(16,)\n"
     ]
    }
   ],
   "source": [
    "for image_batch, labels_batch in train_ds:\n",
    "    print(image_batch.shape)\n",
    "    print(labels_batch.shape)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 配置数据集"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **shuffle() ：** 打乱数据，关于此函数的详细介绍可以参考：https://zhuanlan.zhihu.com/p/42417456\n",
    "- **prefetch() ：** 预取数据，加速运行，其详细介绍可以参考我前两篇文章，里面都有讲解。\n",
    "- **cache() ：** 将数据集缓存到内存当中，加速运行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "AUTOTUNE = tf.data.AUTOTUNE\n",
    "\n",
    "def train_preprocessing(image,label):\n",
    "    return (image/255.0,label)\n",
    "\n",
    "train_ds = (\n",
    "    train_ds.cache()\n",
    "    .shuffle(1000)\n",
    "    .map(train_preprocessing)    # 这里可以设置预处理函数\n",
    "#     .batch(batch_size)           # 在image_dataset_from_directory处已经设置了batch_size\n",
    "    .prefetch(buffer_size=AUTOTUNE)\n",
    ")\n",
    "\n",
    "val_ds = (\n",
    "    val_ds.cache()\n",
    "    .shuffle(1000)\n",
    "    .map(train_preprocessing)    # 这里可以设置预处理函数\n",
    "#     .batch(batch_size)         # 在image_dataset_from_directory处已经设置了batch_size\n",
    "    .prefetch(buffer_size=AUTOTUNE)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. 数据可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 15 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8))  # 图形的宽为10高为5\n",
    "plt.suptitle(\"数据展示\")\n",
    "\n",
    "class_names = [\"乳腺癌细胞\",\"正常细胞\"]\n",
    "\n",
    "for images, labels in train_ds.take(1):\n",
    "    for i in range(15):\n",
    "        plt.subplot(4, 5, i + 1)\n",
    "        plt.xticks([])\n",
    "        plt.yticks([])\n",
    "        plt.grid(False)\n",
    "\n",
    "        # 显示图片\n",
    "        plt.imshow(images[i])\n",
    "        # 显示标签\n",
    "        plt.xlabel(class_names[labels[i]-1])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# 三、构建模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d (Conv2D)              (None, 50, 50, 16)        448       \n",
      "_________________________________________________________________\n",
      "conv2d_1 (Conv2D)            (None, 50, 50, 16)        2320      \n",
      "_________________________________________________________________\n",
      "max_pooling2d (MaxPooling2D) (None, 25, 25, 16)        0         \n",
      "_________________________________________________________________\n",
      "dropout (Dropout)            (None, 25, 25, 16)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_2 (Conv2D)            (None, 25, 25, 16)        2320      \n",
      "_________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2 (None, 12, 12, 16)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_3 (Conv2D)            (None, 12, 12, 16)        2320      \n",
      "_________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2 (None, 6, 6, 16)          0         \n",
      "_________________________________________________________________\n",
      "flatten (Flatten)            (None, 576)               0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 2)                 1154      \n",
      "=================================================================\n",
      "Total params: 8,562\n",
      "Trainable params: 8,562\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "\n",
    "model = tf.keras.Sequential([\n",
    "    tf.keras.layers.Conv2D(filters=16,kernel_size=(3,3),padding=\"same\",activation=\"relu\",input_shape=[img_width, img_height, 3]),\n",
    "    tf.keras.layers.Conv2D(filters=16,kernel_size=(3,3),padding=\"same\",activation=\"relu\"),\n",
    "\n",
    "    tf.keras.layers.MaxPooling2D((2,2)),\n",
    "    tf.keras.layers.Dropout(0.5),\n",
    "    tf.keras.layers.Conv2D(filters=16,kernel_size=(3,3),padding=\"same\",activation=\"relu\"),\n",
    "    tf.keras.layers.MaxPooling2D((2,2)),\n",
    "    tf.keras.layers.Conv2D(filters=16,kernel_size=(3,3),padding=\"same\",activation=\"relu\"),\n",
    "    tf.keras.layers.MaxPooling2D((2,2)),\n",
    "    tf.keras.layers.Flatten(),\n",
    "    tf.keras.layers.Dense(2, activation=\"softmax\")\n",
    "])\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 四、编译"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "model.compile(optimizer=\"adam\",\n",
    "                loss='sparse_categorical_crossentropy',\n",
    "                metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 五、训练模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow.keras.callbacks import ModelCheckpoint, Callback, EarlyStopping, ReduceLROnPlateau, LearningRateScheduler\n",
    "\n",
    "NO_EPOCHS = 100\n",
    "PATIENCE  = 5\n",
    "VERBOSE   = 1\n",
    "\n",
    "# 设置动态学习率\n",
    "annealer = LearningRateScheduler(lambda x: 1e-3 * 0.99 ** (x+NO_EPOCHS))\n",
    "\n",
    "# 设置早停\n",
    "earlystopper = EarlyStopping(monitor='loss', patience=PATIENCE, verbose=VERBOSE)\n",
    "\n",
    "# \n",
    "checkpointer = ModelCheckpoint('best_model.h5',\n",
    "                                monitor='val_accuracy',\n",
    "                                verbose=VERBOSE,\n",
    "                                save_best_only=True,\n",
    "                                save_weights_only=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "671/671 [==============================] - 6s 5ms/step - loss: 0.5599 - accuracy: 0.7103 - val_loss: 0.4927 - val_accuracy: 0.7537\n",
      "\n",
      "Epoch 00001: val_accuracy improved from -inf to 0.75373, saving model to best_model.h5\n",
      "Epoch 2/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.4434 - accuracy: 0.8032 - val_loss: 0.5748 - val_accuracy: 0.7037\n",
      "\n",
      "Epoch 00002: val_accuracy did not improve from 0.75373\n",
      "Epoch 3/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.4194 - accuracy: 0.8164 - val_loss: 0.4491 - val_accuracy: 0.7854\n",
      "\n",
      "Epoch 00003: val_accuracy improved from 0.75373 to 0.78545, saving model to best_model.h5\n",
      "Epoch 4/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.4055 - accuracy: 0.8202 - val_loss: 0.4816 - val_accuracy: 0.7604\n",
      "\n",
      "Epoch 00004: val_accuracy did not improve from 0.78545\n",
      "Epoch 5/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3911 - accuracy: 0.8265 - val_loss: 0.3918 - val_accuracy: 0.8358\n",
      "\n",
      "Epoch 00005: val_accuracy improved from 0.78545 to 0.83582, saving model to best_model.h5\n",
      "Epoch 6/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3756 - accuracy: 0.8336 - val_loss: 0.4277 - val_accuracy: 0.7970\n",
      "\n",
      "Epoch 00006: val_accuracy did not improve from 0.83582\n",
      "Epoch 7/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3689 - accuracy: 0.8364 - val_loss: 0.3648 - val_accuracy: 0.8444\n",
      "\n",
      "Epoch 00007: val_accuracy improved from 0.83582 to 0.84440, saving model to best_model.h5\n",
      "Epoch 8/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3671 - accuracy: 0.8401 - val_loss: 0.3552 - val_accuracy: 0.8526\n",
      "\n",
      "Epoch 00008: val_accuracy improved from 0.84440 to 0.85261, saving model to best_model.h5\n",
      "Epoch 9/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3636 - accuracy: 0.8378 - val_loss: 0.3535 - val_accuracy: 0.8575\n",
      "\n",
      "Epoch 00009: val_accuracy improved from 0.85261 to 0.85746, saving model to best_model.h5\n",
      "Epoch 10/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3528 - accuracy: 0.8434 - val_loss: 0.3615 - val_accuracy: 0.8410\n",
      "\n",
      "Epoch 00010: val_accuracy did not improve from 0.85746\n",
      "Epoch 11/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3507 - accuracy: 0.8467 - val_loss: 0.3973 - val_accuracy: 0.8354\n",
      "\n",
      "Epoch 00011: val_accuracy did not improve from 0.85746\n",
      "Epoch 12/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3457 - accuracy: 0.8467 - val_loss: 0.3237 - val_accuracy: 0.8642\n",
      "\n",
      "Epoch 00012: val_accuracy improved from 0.85746 to 0.86418, saving model to best_model.h5\n",
      "Epoch 13/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3425 - accuracy: 0.8505 - val_loss: 0.3873 - val_accuracy: 0.8414\n",
      "\n",
      "Epoch 00013: val_accuracy did not improve from 0.86418\n",
      "Epoch 14/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3394 - accuracy: 0.8520 - val_loss: 0.3307 - val_accuracy: 0.8683\n",
      "\n",
      "Epoch 00014: val_accuracy improved from 0.86418 to 0.86828, saving model to best_model.h5\n",
      "Epoch 15/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3369 - accuracy: 0.8527 - val_loss: 0.3101 - val_accuracy: 0.8813\n",
      "\n",
      "Epoch 00015: val_accuracy improved from 0.86828 to 0.88134, saving model to best_model.h5\n",
      "Epoch 16/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3285 - accuracy: 0.8561 - val_loss: 0.3602 - val_accuracy: 0.8619\n",
      "\n",
      "Epoch 00016: val_accuracy did not improve from 0.88134\n",
      "Epoch 17/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3320 - accuracy: 0.8529 - val_loss: 0.3900 - val_accuracy: 0.8295\n",
      "\n",
      "Epoch 00017: val_accuracy did not improve from 0.88134\n",
      "Epoch 18/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3307 - accuracy: 0.8565 - val_loss: 0.3064 - val_accuracy: 0.8828\n",
      "\n",
      "Epoch 00018: val_accuracy improved from 0.88134 to 0.88284, saving model to best_model.h5\n",
      "Epoch 19/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3236 - accuracy: 0.8638 - val_loss: 0.3109 - val_accuracy: 0.8776\n",
      "\n",
      "Epoch 00019: val_accuracy did not improve from 0.88284\n",
      "Epoch 20/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3178 - accuracy: 0.8661 - val_loss: 0.2986 - val_accuracy: 0.8884\n",
      "\n",
      "Epoch 00020: val_accuracy improved from 0.88284 to 0.88843, saving model to best_model.h5\n",
      "Epoch 21/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3141 - accuracy: 0.8656 - val_loss: 0.3152 - val_accuracy: 0.8787\n",
      "\n",
      "Epoch 00021: val_accuracy did not improve from 0.88843\n",
      "Epoch 22/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3139 - accuracy: 0.8687 - val_loss: 0.3227 - val_accuracy: 0.8716\n",
      "\n",
      "Epoch 00022: val_accuracy did not improve from 0.88843\n",
      "Epoch 23/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3067 - accuracy: 0.8708 - val_loss: 0.3093 - val_accuracy: 0.8772\n",
      "\n",
      "Epoch 00023: val_accuracy did not improve from 0.88843\n",
      "Epoch 24/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3071 - accuracy: 0.8715 - val_loss: 0.3186 - val_accuracy: 0.8713\n",
      "\n",
      "Epoch 00024: val_accuracy did not improve from 0.88843\n",
      "Epoch 25/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.3030 - accuracy: 0.8713 - val_loss: 0.3525 - val_accuracy: 0.8593\n",
      "\n",
      "Epoch 00025: val_accuracy did not improve from 0.88843\n",
      "Epoch 26/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2991 - accuracy: 0.8741 - val_loss: 0.3630 - val_accuracy: 0.8530\n",
      "\n",
      "Epoch 00026: val_accuracy did not improve from 0.88843\n",
      "Epoch 27/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2982 - accuracy: 0.8735 - val_loss: 0.3503 - val_accuracy: 0.8634\n",
      "\n",
      "Epoch 00027: val_accuracy did not improve from 0.88843\n",
      "Epoch 28/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2988 - accuracy: 0.8721 - val_loss: 0.3196 - val_accuracy: 0.8784\n",
      "\n",
      "Epoch 00028: val_accuracy did not improve from 0.88843\n",
      "Epoch 29/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2895 - accuracy: 0.8780 - val_loss: 0.3095 - val_accuracy: 0.8735\n",
      "\n",
      "Epoch 00029: val_accuracy did not improve from 0.88843\n",
      "Epoch 30/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2930 - accuracy: 0.8779 - val_loss: 0.3249 - val_accuracy: 0.8739\n",
      "\n",
      "Epoch 00030: val_accuracy did not improve from 0.88843\n",
      "Epoch 31/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2911 - accuracy: 0.8783 - val_loss: 0.2767 - val_accuracy: 0.8989\n",
      "\n",
      "Epoch 00031: val_accuracy improved from 0.88843 to 0.89888, saving model to best_model.h5\n",
      "Epoch 32/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2866 - accuracy: 0.8789 - val_loss: 0.3028 - val_accuracy: 0.8828\n",
      "\n",
      "Epoch 00032: val_accuracy did not improve from 0.89888\n",
      "Epoch 33/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2823 - accuracy: 0.8821 - val_loss: 0.2763 - val_accuracy: 0.8940\n",
      "\n",
      "Epoch 00033: val_accuracy did not improve from 0.89888\n",
      "Epoch 34/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2811 - accuracy: 0.8814 - val_loss: 0.2747 - val_accuracy: 0.8981\n",
      "\n",
      "Epoch 00034: val_accuracy did not improve from 0.89888\n",
      "Epoch 35/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2816 - accuracy: 0.8799 - val_loss: 0.2875 - val_accuracy: 0.8877\n",
      "\n",
      "Epoch 00035: val_accuracy did not improve from 0.89888\n",
      "Epoch 36/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2795 - accuracy: 0.8854 - val_loss: 0.3367 - val_accuracy: 0.8545\n",
      "\n",
      "Epoch 00036: val_accuracy did not improve from 0.89888\n",
      "Epoch 37/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2777 - accuracy: 0.8854 - val_loss: 0.2711 - val_accuracy: 0.8970\n",
      "\n",
      "Epoch 00037: val_accuracy did not improve from 0.89888\n",
      "Epoch 38/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2756 - accuracy: 0.8851 - val_loss: 0.2717 - val_accuracy: 0.8959\n",
      "\n",
      "Epoch 00038: val_accuracy did not improve from 0.89888\n",
      "Epoch 39/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2733 - accuracy: 0.8858 - val_loss: 0.2725 - val_accuracy: 0.8944\n",
      "\n",
      "Epoch 00039: val_accuracy did not improve from 0.89888\n",
      "Epoch 40/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2713 - accuracy: 0.8851 - val_loss: 0.3856 - val_accuracy: 0.8478\n",
      "\n",
      "Epoch 00040: val_accuracy did not improve from 0.89888\n",
      "Epoch 41/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2678 - accuracy: 0.8903 - val_loss: 0.2752 - val_accuracy: 0.8955\n",
      "\n",
      "Epoch 00041: val_accuracy did not improve from 0.89888\n",
      "Epoch 42/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2705 - accuracy: 0.8853 - val_loss: 0.2645 - val_accuracy: 0.8989\n",
      "\n",
      "Epoch 00042: val_accuracy did not improve from 0.89888\n",
      "Epoch 43/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2655 - accuracy: 0.8874 - val_loss: 0.2728 - val_accuracy: 0.8944\n",
      "\n",
      "Epoch 00043: val_accuracy did not improve from 0.89888\n",
      "Epoch 44/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2649 - accuracy: 0.8898 - val_loss: 0.2656 - val_accuracy: 0.8959\n",
      "\n",
      "Epoch 00044: val_accuracy did not improve from 0.89888\n",
      "Epoch 45/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2615 - accuracy: 0.8892 - val_loss: 0.2778 - val_accuracy: 0.8959\n",
      "\n",
      "Epoch 00045: val_accuracy did not improve from 0.89888\n",
      "Epoch 46/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2570 - accuracy: 0.8929 - val_loss: 0.2582 - val_accuracy: 0.8996\n",
      "\n",
      "Epoch 00046: val_accuracy improved from 0.89888 to 0.89963, saving model to best_model.h5\n",
      "Epoch 47/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2579 - accuracy: 0.8939 - val_loss: 0.2780 - val_accuracy: 0.8914\n",
      "\n",
      "Epoch 00047: val_accuracy did not improve from 0.89963\n",
      "Epoch 48/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2572 - accuracy: 0.8908 - val_loss: 0.2598 - val_accuracy: 0.8944\n",
      "\n",
      "Epoch 00048: val_accuracy did not improve from 0.89963\n",
      "Epoch 49/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2562 - accuracy: 0.8930 - val_loss: 0.3063 - val_accuracy: 0.8765\n",
      "\n",
      "Epoch 00049: val_accuracy did not improve from 0.89963\n",
      "Epoch 50/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2548 - accuracy: 0.8916 - val_loss: 0.2554 - val_accuracy: 0.9011\n",
      "\n",
      "Epoch 00050: val_accuracy improved from 0.89963 to 0.90112, saving model to best_model.h5\n",
      "Epoch 51/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2521 - accuracy: 0.8960 - val_loss: 0.2671 - val_accuracy: 0.8989\n",
      "\n",
      "Epoch 00051: val_accuracy did not improve from 0.90112\n",
      "Epoch 52/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2508 - accuracy: 0.8956 - val_loss: 0.2712 - val_accuracy: 0.8940\n",
      "\n",
      "Epoch 00052: val_accuracy did not improve from 0.90112\n",
      "Epoch 53/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2477 - accuracy: 0.8951 - val_loss: 0.2550 - val_accuracy: 0.9037\n",
      "\n",
      "Epoch 00053: val_accuracy improved from 0.90112 to 0.90373, saving model to best_model.h5\n",
      "Epoch 54/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2478 - accuracy: 0.8943 - val_loss: 0.2650 - val_accuracy: 0.8993\n",
      "\n",
      "Epoch 00054: val_accuracy did not improve from 0.90373\n",
      "Epoch 55/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2494 - accuracy: 0.8953 - val_loss: 0.2549 - val_accuracy: 0.9026\n",
      "\n",
      "Epoch 00055: val_accuracy did not improve from 0.90373\n",
      "Epoch 56/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2462 - accuracy: 0.8956 - val_loss: 0.2623 - val_accuracy: 0.8989\n",
      "\n",
      "Epoch 00056: val_accuracy did not improve from 0.90373\n",
      "Epoch 57/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2436 - accuracy: 0.8980 - val_loss: 0.2616 - val_accuracy: 0.8989\n",
      "\n",
      "Epoch 00057: val_accuracy did not improve from 0.90373\n",
      "Epoch 58/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2446 - accuracy: 0.8976 - val_loss: 0.2867 - val_accuracy: 0.8847\n",
      "\n",
      "Epoch 00058: val_accuracy did not improve from 0.90373\n",
      "Epoch 59/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2399 - accuracy: 0.8990 - val_loss: 0.2718 - val_accuracy: 0.8869\n",
      "\n",
      "Epoch 00059: val_accuracy did not improve from 0.90373\n",
      "Epoch 60/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2410 - accuracy: 0.8993 - val_loss: 0.3054 - val_accuracy: 0.8750\n",
      "\n",
      "Epoch 00060: val_accuracy did not improve from 0.90373\n",
      "Epoch 61/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2420 - accuracy: 0.8982 - val_loss: 0.2548 - val_accuracy: 0.9004\n",
      "\n",
      "Epoch 00061: val_accuracy did not improve from 0.90373\n",
      "Epoch 62/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2414 - accuracy: 0.8993 - val_loss: 0.2764 - val_accuracy: 0.8933\n",
      "\n",
      "Epoch 00062: val_accuracy did not improve from 0.90373\n",
      "Epoch 63/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2380 - accuracy: 0.9007 - val_loss: 0.2605 - val_accuracy: 0.9011\n",
      "\n",
      "Epoch 00063: val_accuracy did not improve from 0.90373\n",
      "Epoch 64/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2362 - accuracy: 0.9009 - val_loss: 0.2446 - val_accuracy: 0.9049\n",
      "\n",
      "Epoch 00064: val_accuracy improved from 0.90373 to 0.90485, saving model to best_model.h5\n",
      "Epoch 65/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2345 - accuracy: 0.9013 - val_loss: 0.2613 - val_accuracy: 0.8963\n",
      "\n",
      "Epoch 00065: val_accuracy did not improve from 0.90485\n",
      "Epoch 66/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2360 - accuracy: 0.9012 - val_loss: 0.2384 - val_accuracy: 0.9052\n",
      "\n",
      "Epoch 00066: val_accuracy improved from 0.90485 to 0.90522, saving model to best_model.h5\n",
      "Epoch 67/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2346 - accuracy: 0.9019 - val_loss: 0.2438 - val_accuracy: 0.9063\n",
      "\n",
      "Epoch 00067: val_accuracy improved from 0.90522 to 0.90634, saving model to best_model.h5\n",
      "Epoch 68/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2347 - accuracy: 0.9030 - val_loss: 0.2469 - val_accuracy: 0.9034\n",
      "\n",
      "Epoch 00068: val_accuracy did not improve from 0.90634\n",
      "Epoch 69/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2312 - accuracy: 0.9018 - val_loss: 0.2364 - val_accuracy: 0.9082\n",
      "\n",
      "Epoch 00069: val_accuracy improved from 0.90634 to 0.90821, saving model to best_model.h5\n",
      "Epoch 70/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2320 - accuracy: 0.9035 - val_loss: 0.2396 - val_accuracy: 0.9101\n",
      "\n",
      "Epoch 00070: val_accuracy improved from 0.90821 to 0.91007, saving model to best_model.h5\n",
      "Epoch 71/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2290 - accuracy: 0.9047 - val_loss: 0.2495 - val_accuracy: 0.9052\n",
      "\n",
      "Epoch 00071: val_accuracy did not improve from 0.91007\n",
      "Epoch 72/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2308 - accuracy: 0.9025 - val_loss: 0.2416 - val_accuracy: 0.9082\n",
      "\n",
      "Epoch 00072: val_accuracy did not improve from 0.91007\n",
      "Epoch 73/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2271 - accuracy: 0.9064 - val_loss: 0.2413 - val_accuracy: 0.9075\n",
      "\n",
      "Epoch 00073: val_accuracy did not improve from 0.91007\n",
      "Epoch 74/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2288 - accuracy: 0.9051 - val_loss: 0.2391 - val_accuracy: 0.9063\n",
      "\n",
      "Epoch 00074: val_accuracy did not improve from 0.91007\n",
      "Epoch 75/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2244 - accuracy: 0.9066 - val_loss: 0.2343 - val_accuracy: 0.9108\n",
      "\n",
      "Epoch 00075: val_accuracy improved from 0.91007 to 0.91082, saving model to best_model.h5\n",
      "Epoch 76/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2262 - accuracy: 0.9037 - val_loss: 0.2601 - val_accuracy: 0.8996\n",
      "\n",
      "Epoch 00076: val_accuracy did not improve from 0.91082\n",
      "Epoch 77/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2270 - accuracy: 0.9045 - val_loss: 0.2785 - val_accuracy: 0.8866\n",
      "\n",
      "Epoch 00077: val_accuracy did not improve from 0.91082\n",
      "Epoch 78/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2209 - accuracy: 0.9068 - val_loss: 0.2257 - val_accuracy: 0.9097\n",
      "\n",
      "Epoch 00078: val_accuracy did not improve from 0.91082\n",
      "Epoch 79/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2234 - accuracy: 0.9052 - val_loss: 0.2357 - val_accuracy: 0.9123\n",
      "\n",
      "Epoch 00079: val_accuracy improved from 0.91082 to 0.91231, saving model to best_model.h5\n",
      "Epoch 80/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2217 - accuracy: 0.9096 - val_loss: 0.2360 - val_accuracy: 0.9104\n",
      "\n",
      "Epoch 00080: val_accuracy did not improve from 0.91231\n",
      "Epoch 81/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2211 - accuracy: 0.9062 - val_loss: 0.2355 - val_accuracy: 0.9082\n",
      "\n",
      "Epoch 00081: val_accuracy did not improve from 0.91231\n",
      "Epoch 82/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2265 - accuracy: 0.9053 - val_loss: 0.2300 - val_accuracy: 0.9075\n",
      "\n",
      "Epoch 00082: val_accuracy did not improve from 0.91231\n",
      "Epoch 83/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2187 - accuracy: 0.9094 - val_loss: 0.2422 - val_accuracy: 0.9086\n",
      "\n",
      "Epoch 00083: val_accuracy did not improve from 0.91231\n",
      "Epoch 84/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2197 - accuracy: 0.9101 - val_loss: 0.2365 - val_accuracy: 0.9097\n",
      "\n",
      "Epoch 00084: val_accuracy did not improve from 0.91231\n",
      "Epoch 85/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2196 - accuracy: 0.9073 - val_loss: 0.2453 - val_accuracy: 0.9049\n",
      "\n",
      "Epoch 00085: val_accuracy did not improve from 0.91231\n",
      "Epoch 86/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2222 - accuracy: 0.9072 - val_loss: 0.2363 - val_accuracy: 0.9097\n",
      "\n",
      "Epoch 00086: val_accuracy did not improve from 0.91231\n",
      "Epoch 87/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2165 - accuracy: 0.9107 - val_loss: 0.2265 - val_accuracy: 0.9119\n",
      "\n",
      "Epoch 00087: val_accuracy did not improve from 0.91231\n",
      "Epoch 88/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2167 - accuracy: 0.9106 - val_loss: 0.2359 - val_accuracy: 0.9086\n",
      "\n",
      "Epoch 00088: val_accuracy did not improve from 0.91231\n",
      "Epoch 89/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2220 - accuracy: 0.9071 - val_loss: 0.2744 - val_accuracy: 0.8925\n",
      "\n",
      "Epoch 00089: val_accuracy did not improve from 0.91231\n",
      "Epoch 90/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2149 - accuracy: 0.9122 - val_loss: 0.2383 - val_accuracy: 0.9067\n",
      "\n",
      "Epoch 00090: val_accuracy did not improve from 0.91231\n",
      "Epoch 91/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2154 - accuracy: 0.9106 - val_loss: 0.2452 - val_accuracy: 0.9030\n",
      "\n",
      "Epoch 00091: val_accuracy did not improve from 0.91231\n",
      "Epoch 92/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2121 - accuracy: 0.9127 - val_loss: 0.2206 - val_accuracy: 0.9127\n",
      "\n",
      "Epoch 00092: val_accuracy improved from 0.91231 to 0.91269, saving model to best_model.h5\n",
      "Epoch 93/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2127 - accuracy: 0.9109 - val_loss: 0.2280 - val_accuracy: 0.9138\n",
      "\n",
      "Epoch 00093: val_accuracy improved from 0.91269 to 0.91381, saving model to best_model.h5\n",
      "Epoch 94/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2129 - accuracy: 0.9100 - val_loss: 0.2292 - val_accuracy: 0.9138\n",
      "\n",
      "Epoch 00094: val_accuracy did not improve from 0.91381\n",
      "Epoch 95/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2132 - accuracy: 0.9123 - val_loss: 0.2463 - val_accuracy: 0.9049\n",
      "\n",
      "Epoch 00095: val_accuracy did not improve from 0.91381\n",
      "Epoch 96/100\n",
      "671/671 [==============================] - 2s 4ms/step - loss: 0.2109 - accuracy: 0.9122 - val_loss: 0.2285 - val_accuracy: 0.9108\n",
      "\n",
      "Epoch 00096: val_accuracy did not improve from 0.91381\n",
      "Epoch 97/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2116 - accuracy: 0.9110 - val_loss: 0.2301 - val_accuracy: 0.9112\n",
      "\n",
      "Epoch 00097: val_accuracy did not improve from 0.91381\n",
      "Epoch 98/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2131 - accuracy: 0.9118 - val_loss: 0.2319 - val_accuracy: 0.9119\n",
      "\n",
      "Epoch 00098: val_accuracy did not improve from 0.91381\n",
      "Epoch 99/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2091 - accuracy: 0.9149 - val_loss: 0.2311 - val_accuracy: 0.9134\n",
      "\n",
      "Epoch 00099: val_accuracy did not improve from 0.91381\n",
      "Epoch 100/100\n",
      "671/671 [==============================] - 3s 4ms/step - loss: 0.2073 - accuracy: 0.9132 - val_loss: 0.2269 - val_accuracy: 0.9138\n",
      "\n",
      "Epoch 00100: val_accuracy did not improve from 0.91381\n"
     ]
    }
   ],
   "source": [
    "train_model  = model.fit(train_ds,\n",
    "                  epochs=NO_EPOCHS,\n",
    "                  verbose=1,\n",
    "                  validation_data=val_ds,\n",
    "                  callbacks=[earlystopper, checkpointer, annealer])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 六、评估模型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Accuracy与Loss图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "acc = train_model.history['accuracy']\n",
    "val_acc = train_model.history['val_accuracy']\n",
    "\n",
    "loss = train_model.history['loss']\n",
    "val_loss = train_model.history['val_loss']\n",
    "\n",
    "epochs_range = range(len(acc))\n",
    "\n",
    "plt.figure(figsize=(12, 4))\n",
    "plt.subplot(1, 2, 1)\n",
    "\n",
    "plt.plot(epochs_range, acc, label='Training Accuracy')\n",
    "plt.plot(epochs_range, val_acc, label='Validation Accuracy')\n",
    "plt.legend(loc='lower right')\n",
    "plt.title('Training and Validation Accuracy')\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.plot(epochs_range, loss, label='Training Loss')\n",
    "plt.plot(epochs_range, val_loss, label='Validation Loss')\n",
    "plt.legend(loc='upper right')\n",
    "plt.title('Training and Validation Loss')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## 2. 混淆矩阵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "\n",
    "# 定义一个绘制混淆矩阵图的函数\n",
    "def plot_cm(labels, predictions):\n",
    "    \n",
    "    # 生成混淆矩阵\n",
    "    conf_numpy = confusion_matrix(labels, predictions)\n",
    "    # 将矩阵转化为 DataFrame\n",
    "    conf_df = pd.DataFrame(conf_numpy, index=class_names ,columns=class_names)  \n",
    "    \n",
    "    plt.figure(figsize=(8,7))\n",
    "    \n",
    "    sns.heatmap(conf_df, annot=True, fmt=\"d\", cmap=\"BuPu\")\n",
    "    \n",
    "    plt.title('混淆矩阵',fontsize=15)\n",
    "    plt.ylabel('真实值',fontsize=14)\n",
    "    plt.xlabel('预测值',fontsize=14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "val_pre   = []\n",
    "val_label = []\n",
    "\n",
    "for images, labels in val_ds:#这里可以取部分验证数据（.take(1)）生成混淆矩阵\n",
    "    for image, label in zip(images, labels):\n",
    "        # 需要给图片增加一个维度\n",
    "        img_array = tf.expand_dims(image, 0) \n",
    "        # 使用模型预测图片中的人物\n",
    "        prediction = model.predict(img_array)\n",
    "\n",
    "        val_pre.append(class_names[np.argmax(prediction)])\n",
    "        val_label.append(class_names[label])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_cm(val_label, val_pre)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 各项指标评估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "       乳腺癌细胞       0.92      0.90      0.91      1339\n",
      "        正常细胞       0.91      0.92      0.91      1341\n",
      "\n",
      "    accuracy                           0.91      2680\n",
      "   macro avg       0.91      0.91      0.91      2680\n",
      "weighted avg       0.91      0.91      0.91      2680\n",
      "\n",
      "Loss function: 0.22688131034374237, accuracy: 0.9138059616088867\n"
     ]
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "\n",
    "def test_accuracy_report(model):\n",
    "    print(metrics.classification_report(val_label, val_pre, target_names=class_names)) \n",
    "    score = model.evaluate(val_ds, verbose=0)\n",
    "    print('Loss function: %s, accuracy:' % score[0], score[1])\n",
    "    \n",
    "test_accuracy_report(model)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8rc1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
